Wind vane monitoring method and system of wind generating set

Abstract

The invention discloses a wind vane monitoring method and system of a wind generating set, and relates to the technical field of electric digital data processing. The wind vane monitoring method of the wind generating set comprises the following steps of monitoring data acquisition, quality evaluation judgment, monitoring performance evaluation and monitoring optimization judgment. According to the method, the acquisition quality of the wind indicator monitoring data is evaluated, whether the wind indicator monitoring performance coincidence degree evaluation is executed or not is judged, and then the wind indicator monitoring performance coincidence index after the wind indicator monitoring performance coincidence degree evaluation is executed is obtained; and judging whether to execute the wind indicator monitoring optimization or not based on the wind indicator monitoring performance conformity index, then obtaining a wind indicator monitoring optimization index after the wind indicator monitoring optimization is executed, and finally judging whether to execute the wind indicator aging detection or not, thereby achieving the effect of improving the wind indicator monitoring accuracy of the wind generating set. The problem that in the prior art, a wind indicator of a wind generating set is not accurately monitored is solved.

Description

Technical Field

[0001] The invention relates to the technical field of electrical digital data processing, and in particular to a method and system for monitoring a wind vane of a wind turbine generator set. Background Art

[0002] Climate change and environmental issues facing the world have prompted countries to increase their reliance on renewable energy. Wind power generation has become one of the important alternative energy sources. With the rapid development of the wind power industry, intelligence and big data technologies have gradually become the core development trend in the wind power field. Technologies such as data collection and analysis, remote monitoring, and predictive maintenance have become the key to improving the operational efficiency of wind farms. As a basic means of data collection, wind vane monitoring, together with other meteorological data and power generation data, constitutes the basis for the intelligent operation of wind farms.

[0003] The existing wind vane monitoring system for wind turbines mainly relies on a variety of sensor technologies and data processing systems, and is implemented through the cooperation of wind vane sensors and related control systems. Specifically, the wind direction data collected by the wind vane sensor will be transmitted to the control system of the wind turbine through the data acquisition system. The control system of the wind turbine will process and analyze the data collected by the wind vane, and automatically adjust the direction of the wind turbine according to the change in wind direction. With the development of technology, the wind vane monitoring system will develop towards higher accuracy, intelligence and cost-effectiveness, and contribute to the sustainable development of the global wind power industry.

[0004] For example, a patent application with publication number: CN117408015A discloses a multiple wind measurement system design method, a multiple wind measurement system and a calibration method, comprising: arranging multiple groups of wind direction sensors at the tail of the top platform of a wind turbine in a matrix structure; constructing a simulation three-dimensional model, and performing flow field simulation based on multiple groups of wind direction sensors to calculate multi-dimensional wind direction simulation information; calculating the wind direction measurement deviation compliance rate of each monitoring point according to the multi-dimensional wind direction simulation information; determining a preferred column of wind direction sensors based on the wind direction measurement deviation compliance rate of each monitoring point and combining the monitoring point combination data in a superposition and complementary manner; based on the determined preferred column of wind direction sensors, determining a preferred row of wind direction sensors according to the wind direction measurement deviation compliance rate of the monitoring point combination and combining the safety maintenance height, thereby obtaining a multiple wind measurement system including multiple groups of wind direction sensors.

[0005] For example, the invention patent with announcement number: CN109960823B discloses a method and device for determining the equivalent wind speed of a wind turbine generator set, including: obtaining the operating parameter value of the wind turbine generator set; determining the external load parameter value of the wind acting on the wind turbine generator set according to the operating parameter value and the digital equivalent model of the wind turbine generator set; and determining the equivalent wind speed according to the operating parameter value, the external load parameter value and the aerodynamic model of the wind turbine generator set.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] Wind vane monitoring usually relies on sensors to obtain data. The accuracy of the wind vane sensor itself may be affected by the design, manufacturing quality or use environment, resulting in deviations in the measurement results. In addition, wind turbines are often located in remote areas, and external environmental factors may interfere with wind vane monitoring. For example, strong winds, rain and snow may cause sensor signals to fluctuate or be lost, resulting in a decrease in the performance of the monitoring system. At the same time, data transmission may be affected by factors such as signal interference and network instability.

[0008] Another thing that needs to be considered is that if the layout position of the wind vane sensor is unreasonable, it may be blocked by wind turbine blades, towers or other structures, resulting in inaccurate monitoring data collection and inaccurate wind vane monitoring of the wind turbine. Summary of the invention

[0009] The embodiments of the present application solve the problem of inaccurate wind vane monitoring of wind turbines in the prior art by providing a method and system for monitoring the wind vane of a wind turbine, thereby improving the accuracy of wind vane monitoring of a wind turbine.

[0010] The embodiment of the present application provides a method for monitoring a wind vane of a wind turbine generator set, comprising the following steps: S1, collecting wind vane monitoring data of a preset wind turbine generator set within a preset time interval, wherein the wind vane monitoring data includes wind direction data, wind speed data, wind turbine related data and monitoring environment data; S2, evaluating the collection quality of the wind vane monitoring data to obtain a wind vane collection quality evaluation index, and judging whether to perform a wind vane monitoring performance compliance assessment based on the wind vane collection quality evaluation index, wherein the wind vane collection quality evaluation index is used to comprehensively quantify the collection quality of the wind vane monitoring data; S3, obtaining a wind vane monitoring performance compliance index after performing the wind vane monitoring performance compliance assessment, and judging whether to perform wind vane monitoring optimization based on the wind vane monitoring performance compliance index, wherein the wind vane monitoring performance compliance index is used to quantitatively evaluate the wind vane monitoring performance compliance; S4, obtaining a wind vane monitoring optimization index after performing wind vane monitoring optimization, and judging whether to perform wind vane aging detection based on the wind vane collection quality evaluation index, the wind vane monitoring performance compliance index and the wind vane monitoring optimization index, wherein the wind vane monitoring optimization index is used to quantitatively evaluate the effect of wind vane monitoring optimization.

[0011] Furthermore, the specific steps of evaluating the collection quality of wind vane monitoring data to obtain a wind vane collection quality evaluation index are as follows: obtaining a wind turbine measurement evaluation value within a preset time interval, combining the wind turbine measurement evaluation value with the wind turbine reference data obtained from a preset database to obtain a wind turbine data evaluation value, the wind turbine measurement evaluation value represents the wind turbine measurement evaluation related data after de-unitization processing, the wind turbine measurement evaluation value includes the maximum measurement value of generated power, the wind turbine speed measurement value, the wind turbine speed average value and the maximum measurement value of the yaw angle; obtaining a monitoring environment related evaluation value within a preset time interval, processing the monitoring environment related evaluation value to obtain a monitoring environment data evaluation value, the monitoring environment related evaluation value represents the monitoring related evaluation data after de-unitization processing, the monitoring environment related evaluation value includes the environment The wind vane measurement evaluation value within a preset time interval is obtained, and the wind vane measurement evaluation value, the wind turbine data evaluation value, the monitoring environment data evaluation value and the evaluation reference data obtained from the preset database are combined to obtain a wind vane acquisition quality evaluation index, wherein the wind vane measurement evaluation value includes the maximum measurement value of wind direction data and the maximum measurement value of wind speed data, and the evaluation reference data includes evaluation reference values ​​and evaluation reference weights, wherein the evaluation reference values ​​include wind direction data reference values, wind direction data reference maximum difference values ​​and standard wind speed reference values, and the evaluation reference weights include wind vane acquisition quality influencing factors, wind direction data acquisition evaluation weights, wind speed data acquisition evaluation weights, wind turbine data acquisition evaluation weights and environmental data acquisition evaluation weights.

[0012] Furthermore, the method for obtaining the wind vane collection quality evaluation index is as follows:

[0013]

[0014] Where Wf c represents the wind vane acquisition quality assessment index, τ fe represents the influencing factor of wind vane data collection quality, δ1 represents the wind direction data collection assessment weight, δ2 represents the wind speed data collection assessment weight, δ3 represents the wind turbine data collection assessment weight, δ4 represents the environmental data collection assessment weight, D m Indicates the maximum measured value of wind direction data within a preset time interval, D e Indicates the reference value of wind direction data, D max Indicates the maximum difference value of wind direction data reference, W v Indicates the maximum measured value of wind speed data within the preset time interval, W t It represents the standard wind speed reference value, DV represents the wind turbine data evaluation value, and EV represents the monitoring environment data evaluation value.

[0015] Furthermore, the specific steps of judging whether to execute the wind vane monitoring performance compliance assessment based on the wind vane collection quality assessment index are as follows: compare the wind vane collection quality assessment index with the preset collection quality assessment threshold range obtained from the preset database; if the wind vane collection quality assessment index is within the preset collection quality assessment threshold range, then execute the wind vane monitoring performance compliance assessment, and simultaneously obtain the wind vane monitoring performance compliance index after executing the wind vane monitoring performance compliance assessment; if the wind vane collection quality assessment index exceeds the preset collection quality assessment threshold range, then do not execute the wind vane monitoring performance compliance assessment, and simultaneously remind the preset personnel to process the wind vane monitoring data.

[0016] Furthermore, the specific steps for obtaining the wind vane monitoring performance compliance index after executing the wind vane monitoring performance compliance evaluation are as follows: obtaining monitoring performance evaluation related values ​​within a preset time interval, the monitoring performance evaluation related values ​​including the wind vane acquisition quality evaluation index, wind direction data measurement value, wind direction data mean and monitoring response time delay; combining the monitoring performance evaluation related values ​​with the acquisition quality reference optimal threshold, acquisition quality compliance weight, monitoring stability compliance weight and monitoring response compliance weight obtained from a preset database and processing them to obtain the wind vane monitoring performance compliance index.

[0017] Furthermore, the specific steps of judging whether to execute wind vane monitoring optimization based on the wind vane monitoring performance compliance index are as follows: compare the wind vane monitoring performance compliance index with the preset monitoring performance compliance threshold range obtained from a preset database; if the wind vane monitoring performance compliance index is within the preset monitoring performance compliance threshold range, then the wind vane monitoring optimization is not executed, and the wind vane monitoring data, the wind vane collection quality assessment index and the wind vane monitoring performance compliance index are uploaded to cloud storage; if the wind vane monitoring performance compliance index exceeds the preset monitoring performance compliance threshold range, then the wind vane monitoring optimization is executed, and the wind vane monitoring optimization index after the wind vane monitoring optimization is executed is obtained.

[0018] Furthermore, the specific steps of the wind vane monitoring optimization are as follows: A1, optimize the layout height of the wind vane sensor, determine whether the monitored wind vane monitoring performance compliance index is within the preset monitoring performance compliance threshold range, if so, stop the wind vane monitoring optimization, otherwise execute A2; A2, optimize the layout angle of the wind vane sensor, determine whether the monitored wind vane monitoring performance compliance index is within the preset monitoring performance compliance threshold range, if so, stop the wind vane monitoring optimization, otherwise execute A3; A3, perform environmental adaptive optimization on the wind vane sensor, and simultaneously obtain the wind vane monitoring optimization index after the wind vane monitoring optimization is executed.

[0019] Furthermore, the specific steps for obtaining the wind vane monitoring optimization index after performing wind vane monitoring optimization are as follows: obtain the initial monitoring optimization evaluation value before performing wind vane monitoring optimization, the initial monitoring optimization evaluation value includes the initial wind vane acquisition quality evaluation index and the initial wind vane monitoring performance compliance index; obtain the monitoring optimization evaluation value after performing wind vane monitoring optimization, the monitoring optimization evaluation value includes the optimized wind vane acquisition quality evaluation index and the optimized wind vane monitoring performance compliance index; obtain the wind vane monitoring optimization index according to the initial monitoring optimization evaluation value, the monitoring optimization evaluation value and the monitoring optimization correction factor, the acquisition quality optimization weight and the monitoring performance optimization weight obtained from a preset database.

[0020] The embodiment of the present application provides a wind vane monitoring system for a wind turbine generator set, comprising: a monitoring data acquisition module, a quality assessment judgment module, a monitoring performance evaluation module, and a monitoring optimization judgment module; wherein the monitoring data acquisition module is used to collect wind vane monitoring data of a preset wind turbine generator set within a preset time interval, and the wind vane monitoring data includes wind direction data, wind speed data, wind turbine set related data, and monitoring environment data; the quality assessment judgment module is used to evaluate the collection quality of the wind vane monitoring data to obtain a wind vane collection quality assessment index, and judge whether to perform a wind vane monitoring performance compliance degree assessment based on the wind vane collection quality assessment index, and the wind vane collection quality assessment index is used to evaluate the collection quality of the wind vane monitoring data to obtain a wind vane collection quality assessment index, and judge whether to perform a wind vane monitoring performance compliance degree assessment based on the wind vane collection quality assessment index. The quantitative evaluation index is used to comprehensively quantify the collection quality of wind vane monitoring data; the monitoring performance evaluation module is used to obtain the wind vane monitoring performance compliance index after executing the wind vane monitoring performance compliance evaluation, and judge whether to execute wind vane monitoring optimization based on the wind vane monitoring performance compliance index, and the wind vane monitoring performance compliance index is used to quantitatively evaluate the wind vane monitoring performance compliance; the monitoring optimization judgment module is used to obtain the wind vane monitoring optimization index after executing wind vane monitoring optimization, and judge whether to execute wind vane aging detection based on the wind vane collection quality evaluation index and the wind vane monitoring performance compliance index, and the wind vane monitoring optimization index is used to quantitatively evaluate the effect of wind vane monitoring optimization.

[0021] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0022] 1. Evaluate the collection quality of wind vane monitoring data to determine whether to perform wind vane monitoring performance compliance assessment, then obtain the wind vane monitoring performance compliance index after performing the wind vane monitoring performance compliance assessment to determine whether to perform wind vane monitoring optimization, and finally determine whether to perform wind vane aging detection, thereby realizing the evaluation and optimization of wind vane monitoring performance compliance, and then realizing the improvement of wind vane monitoring accuracy of wind turbines, effectively solving the problem of inaccurate wind vane monitoring of wind turbines in the prior art.

[0023] 2. By obtaining the relevant values ​​of monitoring performance evaluation within the preset time interval, and then combining the relevant values ​​of monitoring performance evaluation with the collection quality reference optimal threshold, collection quality compliance weight, monitoring stability compliance weight and monitoring response compliance weight obtained from the preset database, the wind vane monitoring performance compliance index is obtained, thereby realizing the numerical evaluation of the compliance degree of the wind vane monitoring performance, and further realizing a more accurate evaluation of the compliance degree of the wind vane monitoring performance.

[0024] 3. By obtaining the initial monitoring optimization evaluation value before executing the wind vane monitoring optimization, and obtaining the monitoring optimization evaluation value after executing the wind vane monitoring optimization, and then obtaining the wind vane monitoring optimization index according to the initial monitoring optimization evaluation value, the monitoring optimization evaluation value and the monitoring optimization correction factor obtained from the preset database, the collection quality optimization weight and the monitoring performance optimization weight, the numerical evaluation of the wind vane monitoring optimization effect is realized, thereby realizing a more accurate evaluation of the wind vane monitoring optimization effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A flow chart of a method for monitoring a wind vane of a wind turbine generator set provided in an embodiment of the present application;

[0026] Figure 2 A schematic diagram of the change of the wind vane monitoring optimization index provided in the embodiment of the present application, wherein (a) is a schematic diagram of the change of the wind vane monitoring optimization index with the optimized wind vane acquisition quality evaluation index, and (b) is a schematic diagram of the change of the wind vane monitoring optimization index with the optimized wind vane monitoring performance compliance index;

[0027] Figure 3 A schematic structural diagram of a wind vane monitoring system for a wind turbine generator set provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The embodiment of the present application solves the problem of inaccurate wind vane monitoring of wind turbines in the prior art by providing a wind vane monitoring method and system for wind turbines. The method collects wind vane monitoring data of a preset wind turbine within a preset time interval, then evaluates the collection quality of the wind vane monitoring data to obtain a wind vane collection quality evaluation index, determines whether to perform a wind vane monitoring performance compliance assessment based on the wind vane collection quality evaluation index, then obtains the wind vane monitoring performance compliance index after performing the wind vane monitoring performance compliance assessment and determines whether to perform wind vane monitoring optimization, and finally obtains the wind vane monitoring optimization index after performing the wind vane monitoring optimization. Based on the wind vane collection quality evaluation index and the wind vane monitoring performance compliance index, determines whether to perform wind vane aging detection, thereby improving the accuracy of wind vane monitoring of wind turbines.

[0029] The technical solution in the embodiment of the present application is to solve the problem of inaccurate wind vane monitoring of the above-mentioned wind turbine generator set, and the overall idea is as follows:

[0030] The collection quality of wind vane monitoring data is evaluated to determine whether to perform wind vane monitoring performance compliance assessment, and then the wind vane monitoring performance compliance index after performing wind vane monitoring performance compliance assessment is obtained to determine whether to perform wind vane monitoring optimization, and finally the wind vane monitoring optimization index after performing wind vane monitoring optimization is obtained, and it is determined whether to perform wind vane aging detection, thereby achieving the effect of improving the accuracy of wind vane monitoring of wind turbines.

[0031] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0032] like Figure 1 As shown, it is a flow chart of a wind vane monitoring method for a wind turbine generator set provided by an embodiment of the present application, the method comprising the following steps: S1, collecting wind vane monitoring data of a preset wind turbine generator set within a preset time interval, the wind vane monitoring data comprising wind direction data, wind speed data, wind turbine generator set related data and monitoring environment data; S2, evaluating the collection quality of the wind vane monitoring data to obtain a wind vane collection quality evaluation index, judging whether to perform a wind vane monitoring performance compliance evaluation based on the wind vane collection quality evaluation index, and the wind vane collection quality evaluation index is used to comprehensively quantify the wind vane monitoring data The wind vane monitoring performance compliance index is used to quantitatively evaluate the wind vane monitoring performance compliance degree; S4, the wind vane monitoring optimization index is obtained after the wind vane monitoring optimization is performed, and the wind vane monitoring aging detection is determined based on the wind vane monitoring performance compliance index and the wind vane monitoring optimization index. The wind vane monitoring optimization index is used to quantitatively evaluate the effect of wind vane monitoring optimization.

[0033] In this embodiment, wind direction data, i.e., the source angle of the wind relative to the north direction, is obtained by a wind vane sensor deployed on the top of the wind turbine generator set, and wind speed data is obtained by a wind speed sensor deployed on the top of the wind turbine generator set tower.

[0034] It should be understood that the relevant data of wind turbines include wind turbine power generation, wind turbine speed data, and wind turbine yaw angle data. Specifically, the wind turbine power generation is obtained through the power sensor deployed at the output end of the generator, the wind turbine speed data is obtained through the wind turbine speed sensor deployed on the main shaft of the wind turbine, and the wind turbine yaw angle data is obtained through the yaw sensor in the wind turbine yaw system.

[0035] The monitoring environment data includes monitoring environment temperature data, monitoring environment humidity data and monitoring environment air pressure data. Specifically, the monitoring environment data is obtained through a temperature sensor, a humidity sensor and an air pressure sensor deployed on the top of the wind turbine tower.

[0036] By collecting wind vane monitoring data, comprehensive monitoring of data is carried out during the wind vane monitoring performance compliance assessment process, thereby improving the data reliability during the wind vane monitoring process, and further improving the accuracy of the wind vane monitoring performance compliance assessment.

[0037] Furthermore, the specific steps for evaluating the collection quality of wind vane monitoring data to obtain a wind vane collection quality evaluation index are as follows: obtaining a wind turbine measurement evaluation value within a preset time interval, combining the wind turbine measurement evaluation value with the wind turbine reference data obtained from a preset database to obtain a wind turbine data evaluation value (i.e., DV in the wind vane collection quality evaluation index), the wind turbine measurement evaluation value represents the wind turbine measurement evaluation related data after de-unitization processing, the wind turbine measurement evaluation value includes the maximum measurement value of generated power, the wind turbine speed measurement value, the average wind turbine speed, and the maximum measurement value of the yaw angle; obtaining a monitoring environment related evaluation value within a preset time interval, processing the monitoring environment related evaluation value to obtain a monitoring environment data evaluation value (i.e., EV in the wind vane collection quality evaluation index), the monitoring environment related evaluation value represents the monitoring environment related evaluation value after de-unitization processing Evaluation data, monitoring environment related evaluation values ​​include ambient temperature standard deviation, ambient temperature mean, ambient humidity standard deviation, ambient humidity mean, ambient air pressure standard deviation and ambient air pressure mean; obtain wind vane measurement evaluation values ​​within a preset time interval, combine the wind vane measurement evaluation values, wind turbine data evaluation values, monitoring environment data evaluation values ​​with evaluation reference data obtained from a preset database to obtain a wind vane collection quality evaluation index, the wind vane measurement evaluation values ​​include the maximum measurement value of wind direction data and the maximum measurement value of wind speed data, the evaluation reference data include evaluation reference values ​​and evaluation reference weights, the evaluation reference values ​​include wind direction data reference values, wind direction data reference maximum difference values ​​and standard wind speed reference values, the evaluation reference weights include wind vane collection quality influencing factors, wind direction data collection evaluation weights, wind speed data collection evaluation weights, wind turbine data collection evaluation weights and environmental data collection evaluation weights.

[0038] The method for obtaining the wind vane acquisition quality evaluation index is as follows:

[0039]

[0040]

[0041] Where Wf crepresents the wind vane acquisition quality assessment index, τ fe represents the influencing factor of wind vane data collection quality, δ1 represents the wind direction data collection assessment weight, δ2 represents the wind speed data collection assessment weight, δ3 represents the wind turbine data collection assessment weight, δ4 represents the environmental data collection assessment weight, D m Indicates the maximum measured value of wind direction data within a preset time interval, D e Indicates the reference value of wind direction data, D max Indicates the maximum difference value of wind direction data reference, W v Indicates the maximum measured value of wind speed data within the preset time interval, W t represents the standard wind speed reference value, DV represents the wind turbine data evaluation value, EV represents the monitoring environment data evaluation value, P m Indicates the maximum measured value of the generated power within the preset time interval, P e Indicates the reference value of power generation, P max represents the maximum power reference value, n represents the number of the preset time in the preset time interval, n = 1, 2, ..., N, N represents the total number of preset time in the preset time interval, S n represents the fan speed measurement value at the nth preset time within the preset time interval, S′ represents the average fan speed within the preset time interval, and A m Indicates the maximum measured value of the yaw angle within the preset time interval, A e Indicates the yaw angle reference value, A max Indicates the maximum difference value of the yaw angle reference, J w Indicates the standard deviation of the ambient temperature within a preset time interval. Indicates the average ambient temperature within a preset time interval, J s Indicates the standard deviation of ambient humidity within a preset time interval. Represents the average ambient humidity within a preset time interval, J q Indicates the standard deviation of ambient air pressure within a preset time interval. Indicates the average ambient air pressure within a preset time interval.

[0042] In this embodiment, the maximum measured value of the generated power, the maximum measured value of the yaw angle, the maximum measured value of the wind direction data and the maximum measured value of the wind speed data are obtained through the statistical toolbox in MATLAB (such as max(data)), and the maximum measured value of the wind direction data is the maximum value of the wind direction data collected multiple times within a preset time interval; the standard deviation of the ambient temperature, the standard deviation of the ambient humidity and the standard deviation of the ambient pressure are obtained through the statistical toolbox in MATLAB (such as std(data)); the average value of the fan speed, the mean value of the ambient temperature, the mean value of the ambient humidity and the mean value of the ambient pressure are obtained through the statistical toolbox in MATLAB (such as mean(data)).

[0043] Among them, the wind turbine reference data includes a power generation reference value, a maximum power generation reference value, a yaw angle reference value and a yaw angle reference maximum difference value; the power generation reference value is represented by summing and averaging the collected historical power generation, the maximum power generation reference value is represented by the maximum value of the collected historical power generation, the yaw angle reference value is represented by summing and averaging the collected historical yaw angles, and the yaw angle reference maximum difference value is represented by summing and averaging the difference values ​​between the collected historical yaw angles and the standard yaw angle.

[0044] Among them, the wind direction data reference value is represented by the result of summing and averaging the collected historical wind direction data, the wind direction data reference maximum difference value is represented by the result of summing and averaging the collected historical wind direction data and the standard wind direction data, and the standard wind speed reference value is represented by the result of summing and averaging the collected historical wind speeds.

[0045] The wind vane collection quality influencing factor is used to describe the influence of wind vane collection quality influencing factors such as electromagnetic interference on the wind vane collection quality evaluation index. Specifically, the wind vane collection quality influencing factor is the influence factor corresponding to the wind vane collection quality preset in the preset database, which represents the numerical value of the influence of wind vane collection quality influencing factors such as electromagnetic interference on the wind vane collection quality evaluation index. When used, the influence factor corresponding to the preset wind vane collection quality can be directly obtained from the preset database, and the corresponding relationship can be a pre-set mapping relationship. For example, wind vane collection quality influencing factors such as electromagnetic interference intensity and influence factors corresponding to the wind vane collection quality preset in the preset database form a mapping set, and the real-time wind vane collection quality influencing factors such as electromagnetic interference are input into the mapping set to obtain the corresponding weight. The mapping relationship can be one-to-one or many-to-one. In this example, the value range is [0, 1].

[0046] The wind direction data collection assessment weight describes the degree of influence of the wind direction data collection quality (i.e., the difference between the maximum measured value of the wind direction data and the reference value of the wind direction data) on the wind vane collection quality assessment index. It is a numerical value preset in the preset database that represents the degree of influence of the wind direction data collection quality on the wind vane collection quality assessment index. When used, the weight corresponding to the preset wind direction data collection assessment can be directly obtained from the preset database. The corresponding relationship can be a pre-set mapping relationship. For example, the wind direction data collection quality and the weight corresponding to the preset wind direction data collection assessment in the preset database form a mapping set, and the real-time wind direction data collection quality is input into the mapping set to obtain the corresponding weight. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, the value range is [0, 1].

[0047] The wind speed data collection assessment weight quantifies the degree of influence of the wind speed data collection quality (i.e., the difference between the maximum measured value of the wind speed data and the standard wind speed reference value) on the wind vane collection quality assessment index. It is a preset value in the preset database. When used, the weight corresponding to the preset wind speed data collection assessment can be directly obtained from the preset database. The corresponding relationship can be a pre-set mapping relationship. For example, the wind speed data collection quality and the weight corresponding to the preset wind speed data collection assessment in the preset database form a mapping set, and the real-time wind speed data collection quality is input into the mapping set to obtain the corresponding weight. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, the value range is [0, 1].

[0048] The wind turbine data collection assessment weight quantifies the degree of influence of the wind turbine related data collection quality (i.e., the wind turbine data assessment value in the wind vane collection quality assessment index) on the wind vane collection quality assessment index. It is a preset value in the preset database. When used, the weight corresponding to the preset wind turbine data collection assessment can be directly obtained from the preset database. The corresponding relationship can be a pre-set mapping relationship. For example, the wind turbine related data collection quality and the weight corresponding to the preset wind turbine data collection assessment in the preset database form a mapping set, and the real-time wind turbine related data collection quality is input into the mapping set to obtain the corresponding weight. The mapping relationship can be one-to-one or many-to-one. In this example, the value range is [0, 1].

[0049] In this example, the sum of the wind direction data collection assessment weight, wind speed data collection assessment weight, wind turbine data collection assessment weight and environmental data collection assessment weight is 1. The environmental data collection assessment weight is used to describe the degree of influence of the monitoring environment data collection quality on the wind vane collection quality assessment index.

[0050] Specific assumptions: The wind vane data collection quality impact factor is 0.9, the wind direction data collection assessment weight is 0.25, the wind speed data collection assessment weight is 0.25, the wind turbine data collection assessment weight is 0.25, the environmental data collection assessment weight is 0.25, the maximum wind direction data measurement value is 350 degrees, the wind direction data reference value is 180 degrees, the wind direction data reference maximum difference value is 90 degrees, the wind speed data maximum measurement value is 12 meters / second, the standard wind speed reference value is 10 meters / second, the power generation reference value is 1000 watts, and the maximum The maximum power reference value is 1200 watts, the yaw angle reference value is 5 degrees, the yaw angle reference maximum difference value is 10 degrees, the fan speed measurement values ​​are all 1200 rpm, the fan speed average value is 1200 rpm, the ambient temperature average is 22 degrees Celsius, the ambient humidity average is 60 (%), the ambient pressure standard deviation is 1, and the ambient pressure average is 1013 (hPa); the wind vane collection quality evaluation index can be calculated by the above method, and the change statistics of the wind vane collection quality evaluation index are shown in Table 1:

[0051] Table 1 Statistics of changes in wind vane collection quality assessment index

[0052]

[0053] It can be seen from the first and second groups of data in Table 1 that with the decrease of the standard deviation of ambient temperature and the standard deviation of ambient humidity, the wind turbine data evaluation value and the monitoring environment data evaluation value increase accordingly, and then the wind vane collection quality evaluation index increases accordingly; in addition, as in the third, fourth and fifth groups of data, with the decrease of the difference between the maximum measured value of generated power and the reference value of generated power, and the difference between the maximum measured value of yaw angle and the reference value of yaw angle, the wind turbine data evaluation value and the monitoring environment data evaluation value increase accordingly, and then the wind vane collection quality evaluation index also increases accordingly.

[0054] The wind vane collection quality assessment index is used to comprehensively quantify the collection quality of wind vane monitoring data. Among them, changes in the wind turbine data assessment value and the monitoring environment data assessment value directly lead to changes in the wind vane collection quality assessment index. Specifically, with the increase of the wind turbine data assessment value and the monitoring environment data assessment value, the wind vane collection quality assessment index increases accordingly; in addition, the wind vane collection quality assessment index includes multiple parameters, and the various parameters are related and do not exist independently. For example, wind speed directly affects the load of the wind turbine. With the increase of the maximum measured value of the wind speed data, the yaw angle of the wind turbine will increase to adapt to the stronger wind speed, that is, the maximum measured value of the yaw angle will increase accordingly; in addition, with the increase of the maximum measured value of the wind speed data, It also affects the environmental climatic conditions, such as a drop in temperature or an increase in humidity, which increases the average ambient temperature or decreases the average ambient humidity. At the same time, the fan speed is directly affected by the wind speed. As the maximum measured value of the wind speed data increases, the measured value of the fan speed also increases. As the average ambient temperature increases, the friction of the fan increases, which decreases the measured value of the fan speed. Therefore, through a quantitative approach, the correlation and mutual influence between various factors are taken into account, and a comprehensive analysis is conducted to obtain the wind vane collection quality assessment index. This realizes the numerical assessment of the quality of wind vane monitoring data collection, and judges the quality of wind vane monitoring data collection through numerical assessment, thereby achieving a more accurate assessment of the quality of wind vane monitoring data collection.

[0055] Furthermore, the specific steps for determining whether to perform the wind vane monitoring performance compliance assessment based on the wind vane collection quality assessment index are as follows: compare the wind vane collection quality assessment index with the preset collection quality assessment threshold range obtained from a preset database; if the wind vane collection quality assessment index is within the preset collection quality assessment threshold range, then perform the wind vane monitoring performance compliance assessment, and simultaneously obtain the wind vane monitoring performance compliance index after performing the wind vane monitoring performance compliance assessment; if the wind vane collection quality assessment index exceeds the preset collection quality assessment threshold range, then do not perform the wind vane monitoring performance compliance assessment, and simultaneously remind the preset personnel to process the wind vane monitoring data.

[0056] In this embodiment, specifically, the preset acquisition quality assessment threshold range is set by professionals according to standards in the field, for example, the preset acquisition quality assessment threshold range is set to 0.5 to 1; wherein, the wind vane monitoring data processing includes data cleaning and data smoothing.

[0057] Among them, data cleaning refers to the use of visualization tools (such as heat maps) to identify missing values ​​in wind vane monitoring data and fill them in through interpolation methods, such as the mean interpolation method to calculate the mean of the column containing missing values ​​and replace the missing values ​​in the column with the mean; data smoothing refers to the smoothing of wind vane monitoring data through simple moving average; by combining the preset collection quality assessment threshold range to make judgments and process the wind vane monitoring data, a more accurate judgment of the collection quality of wind vane monitoring data is achieved.

[0058] Furthermore, the specific steps for obtaining the wind vane monitoring performance compliance index after executing the wind vane monitoring performance compliance assessment are as follows: obtaining the monitoring performance assessment related values ​​within a preset time interval, the monitoring performance assessment related values ​​including the wind vane acquisition quality assessment index, wind direction data measurement value, wind direction data mean and monitoring response time delay; combining the monitoring performance assessment related values ​​with the acquisition quality reference optimal threshold, acquisition quality compliance weight, monitoring stability compliance weight and monitoring response compliance weight obtained from a preset database and processing them to obtain the wind vane monitoring performance compliance index.

[0059] The method for obtaining the wind vane monitoring performance compliance index is as follows:

[0060]

[0061] Where Wf j represents the compliance index of the wind vane monitoring performance, τ1 represents the compliance weight of the acquisition quality, τ2 represents the compliance weight of the monitoring stability, τ3 represents the compliance weight of the monitoring response, and Wf c Indicates the wind vane collection quality assessment index, ΔY w Indicates the optimal threshold for acquisition quality reference, D m,nrepresents the wind direction data measurement value at the nth preset time within the preset time interval, D′ represents the mean value of the wind direction data within the preset time interval, and ΔT represents the monitoring response time delay.

[0062] In this embodiment, the mean of wind direction data is obtained through the statistical toolbox in MATLAB (such as mean(data)), the evaluation-related delay monitoring response time delay is obtained through the Ping tool, and the optimal threshold for collection quality reference is obtained by setting the middle value of the preset collection quality evaluation threshold range.

[0063] The collection quality compliance weight is a numerical value preset in the preset database that represents the degree of influence of the wind vane collection quality compliance (i.e., the ratio of the wind vane collection quality evaluation index to the collection quality reference optimal threshold) on the wind vane monitoring performance compliance index. When used, the preset collection quality compliance corresponding weight can be directly obtained from the preset database, and the corresponding relationship can be a pre-set mapping relationship. For example, the wind vane collection quality compliance and the collection quality compliance corresponding weight preset in the preset database form a mapping set, and the real-time wind vane collection quality compliance is input into the mapping set to obtain the corresponding weight. The mapping relationship can be one-to-one or many-to-one. In this example, the value range is [0, 1].

[0064] The monitoring stability compliance weight is a numerical value preset in the preset database that represents the degree of influence of the stability of the wind vane monitoring performance (i.e., the square of the difference between the measured value of the wind direction data and the mean value of the wind direction data) on the wind vane monitoring performance compliance index. When used, the corresponding weight of the preset monitoring stability compliance can be directly obtained from the preset database, and the corresponding relationship can be a pre-set mapping relationship. For example, the stability of the wind vane monitoring performance and the corresponding weight of the monitoring stability compliance preset in the preset database form a mapping set, and the real-time wind vane monitoring performance stability is input into the mapping set to obtain the corresponding weight. The mapping relationship can be one-to-one or many-to-one. In this example, the value range is [0, 1].

[0065] In this example, the sum of the collection quality compliance weight, the monitoring stability compliance weight, and the monitoring response compliance weight is 1. The monitoring response compliance weight is used to describe the influence of the wind vane monitoring response on the wind vane monitoring performance compliance index.

[0066] The wind vane monitoring performance compliance index is used to quantitatively evaluate the compliance degree of wind vane monitoring performance. Specifically, the wind vane monitoring performance compliance index includes parameters in multiple aspects, and each parameter is related to each other and does not exist independently. For example, as the monitoring response time delay increases, it indicates that the data collection time in the wind vane monitoring process increases, that is, the wind vane collection quality evaluation index decreases, and then the wind vane monitoring performance compliance index also decreases. Therefore, considering the correlation and mutual influence between various factors, the wind vane monitoring performance compliance index is obtained through comprehensive analysis, which realizes the numerical evaluation of the wind vane monitoring performance compliance degree. The wind vane monitoring performance compliance degree is judged through numerical evaluation, thereby achieving a more accurate evaluation of the wind vane monitoring performance compliance degree.

[0067] Furthermore, the specific steps for determining whether to execute wind vane monitoring optimization based on the wind vane monitoring performance compliance index are as follows: compare the wind vane monitoring performance compliance index with the preset monitoring performance compliance threshold range obtained from the preset database; if the wind vane monitoring performance compliance index is within the preset monitoring performance compliance threshold range, wind vane monitoring optimization is not executed, and the wind vane monitoring data, wind vane collection quality assessment index and wind vane monitoring performance compliance index are backed up in real time and uploaded to cloud storage; if the wind vane monitoring performance compliance index exceeds the preset monitoring performance compliance threshold range, wind vane monitoring optimization is executed, and the wind vane monitoring optimization index after executing the wind vane monitoring optimization is obtained.

[0068] In this embodiment, the preset monitoring performance compliance threshold range is set by professionals based on standards in the field. For example, the preset monitoring performance compliance threshold range is set to 0.7 to 1. By combining the preset monitoring performance compliance threshold range for judgment, a more accurate judgment of the wind vane monitoring performance compliance degree assessment is achieved.

[0069] Furthermore, the specific steps of wind vane monitoring optimization are as follows: A1, optimize the layout height of the wind vane sensor, and determine whether the monitored wind vane monitoring performance compliance index is within the preset monitoring performance compliance threshold range. If so, stop the wind vane monitoring optimization, otherwise execute A2; A2, optimize the layout angle of the wind vane sensor, and determine whether the monitored wind vane monitoring performance compliance index is within the preset monitoring performance compliance threshold range. If so, stop the wind vane monitoring optimization, otherwise execute A3; A3, perform environmental adaptive optimization on the wind vane sensor, and at the same time obtain the wind vane monitoring optimization index after the wind vane monitoring optimization is executed.

[0070] Specifically, the layout height optimization can be based on the initial layout height of the wind vane sensor, which is increased by 20 cm in sequence until the maximum layout height is reached. The maximum layout height can be obtained through a layout height optimization algorithm such as a genetic algorithm; the layout angle optimization algorithm can be based on the initial layout angle of the wind vane sensor, which is increased by 3 degrees in sequence until the maximum layout angle is reached; the wind vane sensor is environmentally adaptively optimized through an adaptive filtering algorithm; and through wind vane monitoring optimization, the optimization reliability is improved when the wind vane monitoring performance is abnormal.

[0071] Furthermore, the specific steps for obtaining the wind vane monitoring optimization index after performing wind vane monitoring optimization are as follows: obtain the initial monitoring optimization evaluation value before performing wind vane monitoring optimization, the initial monitoring optimization evaluation value including the initial wind vane acquisition quality evaluation index and the initial wind vane monitoring performance compliance index; obtain the monitoring optimization evaluation value after performing wind vane monitoring optimization, the monitoring optimization evaluation value including the optimized wind vane acquisition quality evaluation index and the optimized wind vane monitoring performance compliance index; obtain the wind vane monitoring optimization index based on the initial monitoring optimization evaluation value, the monitoring optimization evaluation value, the monitoring optimization correction factor obtained from a preset database, the acquisition quality optimization weight, and the monitoring performance optimization weight.

[0072] The method for obtaining the wind vane monitoring optimization index is as follows:

[0073]

[0074] Where Wf y represents the wind vane monitoring optimization index, γ1 represents the acquisition quality optimization weight, γ2 represents the monitoring performance optimization weight, Wf c,12 represents the optimized wind vane collection quality evaluation index, Wf c,11 represents the initial wind vane acquisition quality assessment index, Wf j,12 Indicates the optimized wind vane monitoring performance compliance index, Wf j,11 Indicates that the initial wind vane monitoring performance meets the index, Represents the monitoring optimization correction factor.

[0075] In this embodiment, the initial wind vane collection quality evaluation index refers to the wind vane collection quality evaluation index before the wind vane monitoring optimization is performed, and the initial wind vane monitoring performance compliance index refers to the wind vane monitoring performance compliance index before the wind vane monitoring optimization is performed.

[0076] The optimized wind vane collection quality assessment index refers to the wind vane collection quality assessment index after the wind vane monitoring optimization is performed, and the optimized wind vane monitoring performance compliance index refers to the wind vane monitoring performance compliance index after the wind vane monitoring optimization is performed.

[0077] The collection quality optimization weight is a numerical value preset in the preset database that represents the degree of influence of the wind vane collection quality optimization situation (i.e., the difference between the optimized wind vane collection quality evaluation index and the initial wind vane collection quality evaluation index) on the wind vane monitoring optimization index. When used, the weight corresponding to the preset collection quality optimization can be directly obtained from the preset database, and the corresponding relationship can be a pre-set mapping relationship. For example, the wind vane collection quality optimization situation and the weight corresponding to the collection quality optimization preset in the preset database form a mapping set, and the real-time wind vane collection quality optimization situation is input into the mapping set to obtain the corresponding weight. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, the value range is [0, 1].

[0078] In this example, the sum of the acquisition quality optimization weight and the monitoring performance optimization weight is 1. The monitoring performance optimization weight is used to describe the influence of the wind vane monitoring performance optimization on the wind vane monitoring optimization index.

[0079] like Figure 2 As shown, it is a schematic diagram of the change of the wind vane monitoring optimization index provided in the embodiment of the present application, wherein: the acquisition quality optimization weight is 0.5, the monitoring performance optimization weight is 0.5, the monitoring optimization correction factor is 0.6, the initial wind vane acquisition quality evaluation index is 0.3, and the initial wind vane monitoring performance compliance index is 0.4; wherein (a) is a schematic diagram of the change of the wind vane monitoring optimization index with the optimized wind vane acquisition quality evaluation index, specifically, the optimized wind vane monitoring performance compliance index is set to 0.9, and as the optimized wind vane acquisition quality evaluation index increases, the wind vane monitoring optimization index increases accordingly; (b) is a schematic diagram of the change of the wind vane monitoring optimization index with the optimized wind vane monitoring performance compliance index, specifically, the optimized wind vane acquisition quality evaluation index is set to 0.8, and as the optimized wind vane monitoring performance compliance index increases, the wind vane monitoring optimization index also increases accordingly.

[0080] The wind vane monitoring optimization index is used to quantitatively evaluate the effect of wind vane monitoring optimization. Specifically, the changes in the optimized wind vane collection quality evaluation index and the optimized wind vane monitoring performance compliance index have an impact on the wind vane monitoring optimization index. Specifically, with the increase of the optimized wind vane collection quality evaluation index and the optimized wind vane monitoring performance compliance index, the wind vane monitoring optimization index increases accordingly; in addition, there is a connection between the optimized wind vane collection quality evaluation index and the optimized wind vane monitoring performance compliance index, and they do not exist independently. For example, with the increase of the optimized wind vane collection quality evaluation index, the optimized wind vane monitoring performance compliance index also increases accordingly. Therefore, through a quantitative approach, the correlation and mutual influence between various factors are taken into account, and the wind vane monitoring optimization index is obtained through a comprehensive analysis, which realizes the numerical evaluation of the wind vane monitoring optimization effect. The wind vane monitoring optimization effect is judged through numerical evaluation, thereby achieving the improvement of the accuracy of the evaluation of the wind vane monitoring optimization effect.

[0081] Furthermore, the specific steps for determining whether to perform wind vane aging detection based on the wind vane collection quality assessment index, the wind vane monitoring performance compliance index and the wind vane monitoring optimization index are as follows: M1, determine whether the obtained wind vane collection quality assessment index is within the preset collection quality assessment threshold range. If the wind vane collection quality assessment index is within the preset collection quality assessment threshold range, execute M2, otherwise, do not perform wind vane aging detection; M2, determine whether the obtained wind vane monitoring performance compliance index is within the preset monitoring performance compliance threshold range. If the wind vane monitoring performance compliance index exceeds the preset monitoring performance compliance threshold range, execute M3, otherwise, do not perform wind vane aging detection; M3, determine whether the obtained wind vane monitoring optimization index is within the preset monitoring optimization threshold range. If the wind vane monitoring optimization index is within the preset monitoring optimization threshold range, do not perform wind vane aging detection. Otherwise, perform wind vane aging detection.

[0082] In this embodiment, the weather vane aging detection is performed by a fault diagnosis tool (such as Sensor Diagnostics Software); wherein the preset monitoring optimization threshold range is obtained from a preset database, specifically, the preset monitoring optimization threshold range is set by professionals according to standards in the field, for example, the preset monitoring optimization threshold range is set to 0.6 to 1; by making a judgment in combination with the preset monitoring optimization threshold range, a more accurate judgment of the evaluation of the wind vane monitoring optimization effect is achieved.

[0083] like Figure 3As shown, it is a structural schematic diagram of a wind vane monitoring system for a wind turbine generator set provided in an embodiment of the present application. A wind vane monitoring system for a wind turbine generator set provided in an embodiment of the present application includes: a monitoring data acquisition module, a quality assessment judgment module, a monitoring performance assessment module, and a monitoring optimization judgment module; wherein the monitoring data acquisition module is used to collect wind vane monitoring data of a preset wind turbine generator set within a preset time interval, and the wind vane monitoring data includes wind direction data, wind speed data, wind turbine generator set related data, and monitoring environment data; the quality assessment judgment module is used to evaluate the collection quality of the wind vane monitoring data to obtain a wind vane collection quality assessment index, and judge whether to execute the wind direction optimization based on the wind vane collection quality assessment index. The wind vane monitoring performance compliance degree is evaluated, and the wind vane collection quality evaluation index is used to comprehensively quantify the collection quality of wind vane monitoring data; the monitoring performance evaluation module is used to obtain the wind vane monitoring performance compliance index after executing the wind vane monitoring performance compliance degree evaluation, and judge whether to execute wind vane monitoring optimization based on the wind vane monitoring performance compliance index, and the wind vane monitoring performance compliance index is used to quantitatively evaluate the wind vane monitoring performance compliance degree; the monitoring optimization judgment module is used to obtain the wind vane monitoring optimization index after executing wind vane monitoring optimization, and judge whether to execute wind vane aging detection based on the wind vane collection quality evaluation index and the wind vane monitoring performance compliance index, and the wind vane monitoring optimization index is used to quantitatively evaluate the effect of wind vane monitoring optimization.

[0084] In this embodiment, by collecting wind vane monitoring data, the wind vane monitoring data collection quality is evaluated and the wind vane monitoring performance compliance is evaluated and optimized, thereby improving the wind vane monitoring quality of the wind turbine generator set.

[0085] To summarize, the embodiment of the present application evaluates the collection quality of wind vane monitoring data to determine whether to perform a wind vane monitoring performance compliance assessment, then obtains the wind vane monitoring performance compliance index after performing the wind vane monitoring performance compliance assessment to determine whether to perform wind vane monitoring optimization, and finally determines whether to perform wind vane aging detection, thereby achieving an assessment and optimization of the wind vane monitoring performance compliance, and further achieving improved accuracy in wind vane monitoring of wind turbines, effectively solving the problem of inaccurate wind vane monitoring of wind turbines in the prior art.

[0086] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0087] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0088] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0089] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0090] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0091] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for monitoring a wind vane of a wind turbine generator set, characterized in that: The following steps are involved: S1, collecting wind vane monitoring data of a preset wind turbine generator set within a preset time interval, wherein the wind vane monitoring data includes wind direction data, wind speed data, wind turbine generator set related data and monitoring environment data; S2, evaluating the collection quality of the wind vane monitoring data to obtain a wind vane collection quality evaluation index, and judging whether to perform the wind vane monitoring performance compliance evaluation based on the wind vane collection quality evaluation index, wherein the wind vane collection quality evaluation index is used to comprehensively quantify the collection quality of the wind vane monitoring data; S3, obtaining a wind vane monitoring performance compliance index after executing the wind vane monitoring performance compliance evaluation, and judging whether to execute the wind vane monitoring optimization based on the wind vane monitoring performance compliance index, wherein the wind vane monitoring performance compliance index is used to quantitatively evaluate the wind vane monitoring performance compliance; S4, obtaining the wind vane monitoring optimization index after executing the wind vane monitoring optimization, judging whether to execute the wind vane aging detection according to the wind vane collection quality evaluation index, the wind vane monitoring performance compliance index and the wind vane monitoring optimization index, the wind vane monitoring optimization index is used to quantitatively evaluate the effect of the wind vane monitoring optimization.

2. A method for monitoring a wind vane of a wind turbine generator set as claimed in claim 1, characterized in that: The specific steps of evaluating the collection quality of the wind vane monitoring data to obtain the wind vane collection quality evaluation index are as follows: Obtaining a wind turbine generator set measurement evaluation value within a preset time interval, combining the wind turbine generator set measurement evaluation value with wind turbine generator set reference data obtained from a preset database to obtain a wind turbine generator set data evaluation value, wherein the wind turbine generator set measurement evaluation value represents wind turbine generator set measurement evaluation related data after de-normalization, and the wind turbine generator set measurement evaluation value includes a maximum measurement value of generated power, a wind turbine speed measurement value, an average wind turbine speed, and a maximum measurement value of a yaw angle; Obtaining a monitoring environment related assessment value within a preset time interval, and processing the monitoring environment related assessment value to obtain a monitoring environment data assessment value, wherein the monitoring environment related assessment value represents the monitoring related assessment data after de-unitization processing, and the monitoring environment related assessment value includes an ambient temperature standard deviation, an ambient temperature mean, an ambient humidity standard deviation, an ambient humidity mean, an ambient pressure standard deviation, and an ambient pressure mean; Acquire a wind vane measurement evaluation value within a preset time interval, and combine the wind vane measurement evaluation value, the wind turbine data evaluation value, the monitoring environment data evaluation value with the evaluation reference data acquired from a preset database to obtain a wind vane acquisition quality evaluation index, wherein the wind vane measurement evaluation value includes a maximum measurement value of wind direction data and a maximum measurement value of wind speed data, and the evaluation reference data includes an evaluation reference value and an evaluation reference weight, and the evaluation reference value includes a wind direction data reference value, a wind direction data reference maximum difference value, and a standard wind speed reference value, and the evaluation reference weight includes a wind vane acquisition quality influencing factor, a wind direction data acquisition evaluation weight, a wind speed data acquisition evaluation weight, a wind turbine data acquisition evaluation weight, and an environmental data acquisition evaluation weight.

3. A method for monitoring the wind vane of a wind turbine generator set as claimed in claim 2, characterized in that: The method for obtaining the wind vane acquisition quality evaluation index is as follows: Where Wf c represents the wind vane acquisition quality assessment index, τ fe represents the influencing factor of wind vane data collection quality, δ1 represents the wind direction data collection assessment weight, δ2 represents the wind speed data collection assessment weight, δ3 represents the wind turbine data collection assessment weight, δ4 represents the environmental data collection assessment weight, D m Indicates the maximum measured value of wind direction data within a preset time interval, D e Indicates the reference value of wind direction data, D max Indicates the maximum difference value of wind direction data reference, W v Indicates the maximum measured value of wind speed data within the preset time interval, W t It represents the standard wind speed reference value, DV represents the wind turbine data evaluation value, and EV represents the monitoring environment data evaluation value.

4. A method for monitoring a wind vane of a wind turbine generator set as claimed in claim 1, characterized in that: The specific steps of judging whether to perform the wind vane monitoring performance compliance evaluation based on the wind vane collection quality evaluation index are as follows: comparing the wind vane acquisition quality assessment index with a preset acquisition quality assessment threshold range obtained from a preset database; If the wind vane acquisition quality assessment index is within the preset acquisition quality assessment threshold range, the wind vane monitoring performance compliance assessment is performed, and the wind vane monitoring performance compliance index after the wind vane monitoring performance compliance assessment is performed is obtained; If the wind vane collection quality assessment index exceeds the preset collection quality assessment threshold range, the wind vane monitoring performance compliance assessment will not be performed, and the preset personnel will be reminded to process the wind vane monitoring data.

5. A method for monitoring the wind vane of a wind turbine generator set as claimed in claim 4, characterized in that: The specific steps of obtaining the wind vane monitoring performance compliance index after executing the wind vane monitoring performance compliance evaluation are as follows: Acquire monitoring performance evaluation related values ​​within a preset time interval, wherein the monitoring performance evaluation related values ​​include a wind vane acquisition quality evaluation index, a wind direction data measurement value, a wind direction data mean value, and a monitoring response time delay; The wind vane monitoring performance compliance index is obtained by combining the monitoring performance evaluation related values ​​with the collection quality reference optimal threshold, collection quality compliance weight, monitoring stability compliance weight and monitoring response compliance weight obtained from the preset database.

6. A method for monitoring a wind vane of a wind turbine generator set as claimed in claim 1, characterized in that: The specific steps of judging whether to perform wind vane monitoring optimization based on the wind vane monitoring performance compliance index are as follows: comparing the wind vane monitoring performance compliance index with a preset monitoring performance compliance threshold range obtained from a preset database; If the wind vane monitoring performance compliance index is within the preset monitoring performance compliance threshold range, the wind vane monitoring optimization is not performed, and the wind vane monitoring data, the wind vane acquisition quality assessment index, and the wind vane monitoring performance compliance index are uploaded to the cloud storage; If the wind vane monitoring performance compliance index exceeds the preset monitoring performance compliance threshold range, the wind vane monitoring optimization is performed, and the wind vane monitoring optimization index after the wind vane monitoring optimization is performed is obtained.

7. A method for monitoring a wind vane of a wind turbine generator set as claimed in claim 4, characterized in that: The specific steps of the wind vane monitoring optimization are as follows: A1, optimize the layout of the wind vane sensor, determine whether the wind vane monitoring performance compliance index is within the preset monitoring performance compliance threshold range, if so, stop the wind vane monitoring optimization, otherwise execute A2; A2, optimize the layout angle of the wind vane sensor, and determine whether the wind vane monitoring performance compliance index is within the preset monitoring performance compliance threshold range. If so, stop the wind vane monitoring optimization, otherwise execute A3; A3, performing environmental adaptive optimization on the wind vane sensor, and obtaining a wind vane monitoring optimization index after executing the wind vane monitoring optimization.

8. A method for monitoring a wind vane of a wind turbine generator set as claimed in claim 7, characterized in that: The specific steps of obtaining the wind vane monitoring optimization index after performing the wind vane monitoring optimization are as follows: Acquire an initial monitoring optimization evaluation value before executing the wind vane monitoring optimization, wherein the initial monitoring optimization evaluation value includes an initial wind vane acquisition quality evaluation index and an initial wind vane monitoring performance compliance index; Obtaining a monitoring optimization evaluation value after executing the wind vane monitoring optimization, wherein the monitoring optimization evaluation value includes an optimized wind vane acquisition quality evaluation index and an optimized wind vane monitoring performance compliance index; The wind vane monitoring optimization index is obtained based on the initial monitoring optimization evaluation value, the monitoring optimization evaluation value and the monitoring optimization correction factor obtained from the preset database, the collection quality optimization weight and the monitoring performance optimization weight.

9. A method for monitoring a wind vane of a wind turbine generator set as claimed in claim 1, characterized in that: The specific steps of judging whether to perform the wind vane aging detection according to the wind vane collection quality evaluation index, the wind vane monitoring performance compliance index and the wind vane monitoring optimization index are as follows: M1, judging whether the acquired wind vane acquisition quality assessment index is within the preset acquisition quality assessment threshold range, if the wind vane acquisition quality assessment index is within the preset acquisition quality assessment threshold range, executing M2, otherwise, not executing the wind vane aging detection; M2, judging whether the acquired wind vane monitoring performance compliance index is within the preset monitoring performance compliance threshold range, if the wind vane monitoring performance compliance index exceeds the preset monitoring performance compliance threshold range, executing M3, otherwise, not executing the wind vane aging detection; M3, determine whether the acquired wind vane monitoring optimization index is within the preset monitoring optimization threshold range. If the wind vane monitoring optimization index is within the preset monitoring optimization threshold range, the wind vane aging detection is not performed. Otherwise, the wind vane aging detection is performed.

10. A wind vane monitoring system for a wind turbine generator set, characterized in that: include: Monitoring data collection module, quality assessment and judgment module, monitoring performance evaluation module, monitoring optimization and judgment module; Wherein, the monitoring data acquisition module is used to collect the wind vane monitoring data of the preset wind turbine generator set within the preset time interval, and the wind vane monitoring data includes wind direction data, wind speed data, wind turbine generator set related data and monitoring environment data; The quality assessment judgment module is used to evaluate the collection quality of the wind vane monitoring data to obtain a wind vane collection quality assessment index, and judge whether to perform the wind vane monitoring performance compliance assessment based on the wind vane collection quality assessment index. The wind vane collection quality assessment index is used to comprehensively quantify the collection quality of the wind vane monitoring data; The monitoring performance evaluation module is used to obtain the wind vane monitoring performance compliance index after executing the wind vane monitoring performance compliance evaluation, and determine whether to execute the wind vane monitoring optimization based on the wind vane monitoring performance compliance index, and the wind vane monitoring performance compliance index is used to quantitatively evaluate the wind vane monitoring performance compliance; The monitoring optimization judgment module is used to obtain the wind vane monitoring optimization index after executing the wind vane monitoring optimization, and to determine whether to perform wind vane aging detection based on the wind vane collection quality evaluation index and the wind vane monitoring performance compliance index. The wind vane monitoring optimization index is used to quantitatively evaluate the effect of wind vane monitoring optimization.

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